---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: out
  results: []
---

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# mistral-alpaca-finetune

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the mhenrichsen/alpaca_2k_test dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9808

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9152        | 0.01  | 1    | 0.9037          |
| 0.9101        | 0.15  | 18   | 0.8461          |
| 0.7589        | 0.3   | 36   | 0.8437          |
| 0.8274        | 0.45  | 54   | 0.8441          |
| 0.7255        | 0.61  | 72   | 0.8435          |
| 0.85          | 0.76  | 90   | 0.8419          |
| 0.9083        | 0.91  | 108  | 0.8408          |
| 0.3208        | 1.06  | 126  | 0.9177          |
| 0.3738        | 1.21  | 144  | 0.8924          |
| 0.4034        | 1.36  | 162  | 0.8914          |
| 0.3936        | 1.51  | 180  | 0.9032          |
| 0.3188        | 1.66  | 198  | 0.9001          |
| 0.4331        | 1.82  | 216  | 0.8973          |
| 0.3946        | 1.97  | 234  | 0.8963          |
| 0.1531        | 2.12  | 252  | 0.9653          |
| 0.1741        | 2.27  | 270  | 0.9841          |
| 0.2371        | 2.42  | 288  | 0.9784          |
| 0.271         | 2.57  | 306  | 0.9801          |
| 0.2632        | 2.72  | 324  | 0.9808          |
| 0.1691        | 2.87  | 342  | 0.9808          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0